In a recent study published in the journal Science Advances, researchers analyzed survey data from individuals in India to understand mortality and life expectancy during the coronavirus disease 2019 (COVID-19) pandemic. They found that life expectancy in India fell by 2.6 years in 2020, with 1.19 million excess deaths, disproportionately affecting younger age groups, females, and marginalized social groups.

Background

The COVID-19 pandemic caused significant global mortality while reducing global life expectancy. In high-income countries (HICs), robust surveillance systems recorded notable declines in life expectancy and increased disparities across socioeconomic status and race. However, the extent and social variation of COVID-19 deaths in low- and middle-income countries remain poorly understood due to limited resources and inadequate health response and data quality.

Given that India is the world’s most populated country with a highly diverse demographic, accurately estimating pandemic mortality is crucial for understanding the global impact of the pandemic.

Therefore, researchers in the present study estimated changes in life expectancy by social group and gender from 2019 to 2020 in India, where it is estimated that one-third of the global excess deaths from the pandemic may have occurred. Using high-quality data from India’s National Family Health Survey-5 (NFHS-5), the researchers aimed to address the current gaps in knowledge caused by incomplete data. They also estimated monthly excess mortality in 2020 relative to baseline, enabling comparisons of pandemic mortality impacts across different populations.

About the study

In the present study, a “subsample” from the NFHS-5 data was used (n = 765,180), which included households interviewed in 2021, representing 23.2% of India’s population. Mortality was estimated for 2018, 2019, and 2020 using retrospective questions, ensuring unbiased comparisons. Initially, life expectancy at birth was compared between 2019 and 2020 for both the entire subsample and separately for the two genders. Further, high-caste Hindus were compared to the following social groups: Scheduled Castes (SCs), Scheduled Tribes (STs), Muslims, and Other Backward Classes (OBCs). Retrospective questions on household deaths were used to estimate age-specific mortality.

Additional data were obtained for comparison from the Sample Registration System, Civil Registration System, World Health Organization (WHO), and United Nations World Population Prospects. Robustness checks were performed to ensure the representativeness of the subsample and address potential concerns related to data quality and recall bias.

Results and discussion

The findings revealed a 2.6-year reduction in life expectancy at birth from 2019 to 2020, a decline more severe than in HICs and greater than previous estimates for India. This decline was notably pronounced among the youngest and oldest age groups, with higher-than-expected mortality among older individuals, possibly due to higher infection fatality rates and indirect effects of the pandemic.

Gender disparities were also evident, with females experiencing a larger decline in life expectancy (3.6 years) compared to males (2.6 years), likely due to gender inequality in healthcare and resource allocation. Social disparities were also highlighted, with SC, STs, and Muslims experiencing a greater reduction in life expectancy compared to high-caste Hindus. Muslims saw a 5.4-year decline, STs a 4.1-year decline, and SCs a 2.7-year decline, adding to pre-existing inequalities.

The study estimated a 17.1% increase in mortality during 2020 compared to 2019, with significant peaks in the last four months of 2020. If extrapolated to the entire country, this suggested about 1.19 million excess deaths in 2020, substantially higher than official COVID-19 death counts and previous WHO estimates. The excess mortality patterns were validated with civil registration data in states with high death registration rates.

The NFHS-5 data provided valuable insights into pandemic mortality, addressing gaps left by administrative data and non-representative surveys. The study is strengthened by its use of comprehensive, high-quality data from the NFHS-5, providing a large and diverse sample for unbiased mortality analysis. The observed patterns suggest that indirect effects of the pandemic and lockdown might have contributed to increased mortality.

Still, more data are required to differentiate between the direct and indirect impacts of COVID-19 on mortality in 2020 and beyond. Additionally, geographic clustering and compositional differences in the subsample are found to potentially limit the generalizability of the findings to the national level.

Conclusion

In conclusion, the study highlights significant life expectancy declines and increased mortality in India during COVID-19, especially among females, younger age groups, and marginalized communities. It emphasizes the value of high-quality data for understanding such crises and demonstrates effective retrospective mortality estimation methods.

In the future, studies could explore gender and age disparities, differentiate between direct and indirect mortality impacts, broaden geographic coverage, and enhance data quality. Targeted interventions for disadvantaged groups are essential to address exacerbated inequalities and improve crisis responses in the future.